Heterogeneity and Cross-Country Spillovers in Macroeconomic-Financial Linkages

Ciccarelli, Matteo; Ortega, Eva; Valderrama, María Teresa

doi:10.2139/ssrn.2192417

Cited by 65 publications

(21 citation statements)

References 45 publications

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“…Conversely, Spanish macroeconomic or financial cycles cannot generate sizable transmission mechanisms. Moreover, we find that the transmission of financial shocks affects national GDPs, so that not only real international cycles seem to matter, but also financial cycles have important real spillovers, in accordance with the results of Ciccarelli, Ortega and Valderrama (2012).…”

Section: Introductionsupporting

confidence: 88%

Euro Area business cycles in turbulent times: convergence or decoupling?

Ferroni

Klaus

2015

Applied Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe study the business cycle properties of the four largest euro area economies in the wake of the recent recession episodes. The analysis is based on the factors estimated from a multi-country and multi-sector data-rich environment. We measure alikeness of business cycles by studying the synchronization of up and down phases, the convergence properties of country fluctuations towards the euro area cycles and the contribution of the euro area factor to national GDP volatilities. While the economic fluctuations of the four euro area member states were similar before the global financial turmoil, we gather compelling evidence of an asymmetric behaviour of Spanish fluctuations relative to the euro area one. The paper studies the statistical properties of the business cycles of the four largest euro area economies, Germany, France, Italy and Spain in the wake of the recent recession episodes. In particular, we study the degree of (a)symmetry by looking at the synchronization of up and down phases, the convergence properties of country fluctuations towards the euro area cycles and the contribution of the euro area factor to the volatility of national GDPs. Our empirical investigation brings the following results for the four largest euro area economies. First, data support the idea of a substantial economic integration among France, Germany and (perhaps surprisingly) Italy.The estimated national and sector-specific characteristics appear to co-move strongly, to be well synchronized and to have converged to a common euro area factor. Conversely, Spanish business cycles appear to be decoupled from the rest of the euro area; in particular, the Spanish economic activity seemed to be overheated before the crisis and over-depressed in the aftermath. Our empirical evidence supports the view of an imperfect synchronization relative to the euro area factor and suggests a sluggish and incomplete convergence of the Spanish factor to the euro area one. Moreover, contrary to the common wisdom that identifies the European sovereign debt crisis as the trigger of the growing gap among euro area countries, our subsample analysis locates the economic decoupling of Spain 1 year before that. Second, in accordance with the behaviour of the estimated factors, the main driver of domestic fluctuations (for France, Germany and Italy) is the common euro area factor which explains more than half of the domestic GDP volatility and its components. The fl...

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Section: Introductionsupporting

confidence: 88%

Euro Area business cycles in turbulent times: convergence or decoupling?

Ferroni

Klaus

2015

Applied Economics

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“…RELATED LITERATURE AND FEATURES OF OUR APPROACH There is a growing, but still small, empirical literature which looks at the role of financial variables for the macroeconomy in a time-varying parameter setup. Time series applications for the USA include Balke (2000), Davig and Haikko (2010), Kaufmann and Valderrama (2010), Guerrieri and Iacoviello (2012), Hubrich and Tetlow (2015), Nason and Tallman (2015), Abbate et al (2015), Ciccarelli et al (2012) and Gambetti and Musso (2012). An overview of previous work (including work for countries other than the USA) is presented in the online Appendix (supporting information).…”

Section: Introductionmentioning

confidence: 99%

Time Variation in Macro‐Financial Linkages

Prieto

Eickmeier

Marcellino

2016

J of Applied Econometrics

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Reproduction permitted only if source is stated.ISBN 978-3-86558-907-1 (Printversion) Non-technical summary None of the macroeconomic models commonly used in academic research and in policy institutions was able to predict the strong economic downturn following the Global Financial Crisis. Two main shortcomings of the standard macro modeling approach have been identi…ed: the lack of …nancial variables in these models and the lack of a time-varying relationship between …nancial and macroeconomic variables.We try to overcome these shortcomings and incorporate a few key …nancial indicators in an otherwise standard Bayesian macroeconomic vector autoregressive model (VAR) for the US and estimate that model over the period 1958Q1-2012Q2. The VAR includes GDP growth, GDP de ‡ator in ‡ation, house price in ‡ation, the corporate bond spread, stock price in ‡ation and the Federal Funds rate. In order to account for possible time variation in the relationship between …nancial indicators and the macroeconomy, we allow for continuous changes in the autoregressive coe¢ cients, contemporaneous relations and stochastic volatilities. This re ‡ects the fact that time variation in the shock transmission can occur because of permanent structural changes such as …nancial globalization, regulatory changes or changes in the conduct of monetary policy or because of temporary changes due to agency problems between lenders and borrowers which are more pronounced in …nancial crisis periods than in normal periods.Based on our estimated time-varying parameter VAR, we look at the sum of the contributions of shocks to each individual …nancial indicator to GDP growth as a measure of the overall importance of the …nancial sector as origin of shocks for the macroeconomy. We then shed light on the underlying sources of time variation. We assess the contribution of unexpected changes in individual …nancial variables to GDP growth over time and look at possible changes in the volatility of …nancial shocks and in their impact on GDP growth. Finally, we compare …nancial shock contributions estimated from the model with those estimated from a constant parameter VAR and a VAR in which we replace the …nancial variables with the National Financial Conditions Index published by the Federal Reserve Bank of Chicago, a latent factor extracted from a very large number of …nancial variables.Our main …ndings are: (i) The contribution of …nancial shocks to the forecast error variance of GDP growth ‡uctuates considerably over time, from about 20 percent in normal times to roughly 50 percent over the global …nancial crisis period. (ii) The Great Recession and the subsequent weak recovery can largely be traced back to negative housing shocks. (iii) Housing shocks have become more important for the real economy since the early-2000s, and negative housing shocks are more important than positive ones. Die wichtigsten Erkenntnisse lauten: a) Der Beitrag …nanzieller Schocks zur Prognosefehlervarianz des BIP-Wachstums schwankt im Zeitverlauf erheblich und reicht von etw...

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“…The two papers most closely related to our analysis are Ciccarelli, Ortega and Valderrama (2012) and Prieto, Eickmeier and Marcellino (2013), which are both based on TVP-VAR models. On the one hand, unlike Ciccarelli, Ortega and Valderrama (2012), we allow for stochastic volatility (whereas they assume time variation only in the autoregressive coefficient The variables in y t are the real GDP growth rate, the inflation rate, the short-term interest rate, the growth rate of the stock of credit to the private sector, and an indicator of financial stress especially designed for the euro area (the Composite Indicator of Systemic Stress, or CISS, based on the work of Holló, Kremer, and Lo Duca, 2012). All the variables except the financial stress indicator and the short-term interest rate are expressed in quarter-on-quarter growth rates.…”

Section: The Tvp-var Model Specification and The Datasetmentioning

confidence: 99%